Three-dimensional bioprinting of patient-derived Gastrointestinal stromal tumor: a novel platform for precision oncology and drug response profiling.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) exhibit significant heterogeneity, posing substantial challenges for personalized treatment strategies. Patients often display varied responses to different therapeutic agents and dosages. Currently, the absence of robust and physiologically relevant in vitro models for GISTs impedes accurate prediction of therapeutic efficacy, thereby constraining the advancement of effective treatment strategies. Traditional 2D cell cultures fail to replicate the tumor microenvironment (TME) and lack patient-specific characteristics, limiting their predictive value. In contrast, three-dimensional bioprinting (3DP) technology faithfully recapitulates key histological architecture and molecular features of their parental tumors, enhancing the physiological relevance of in vitro models. METHODS: We employed patient-derived 3DP-GIST models via 3D bioprinting technology, followed by comprehensive histopathological, genomic, and transcriptomic analyses. Subsequently, we applied clinically approved targeted therapeutic agents to perform drug screening and response prediction on the 3DP-GIST models. The drug sensitivity profiles obtained from these models were then correlated with retrospective clinical data and patient follow-up records to assess the models' potential in guiding the selection and prediction of effective GIST therapies. RESULTS: In our study, we successfully constructed 12 patient-derived 3DP-GIST models. Histopathological assessments, whole-exome sequencing (WES), and transcriptomic analyses confirmed that these models accurately recapitulate the histological architecture, biomarker expression, and molecular features of their corresponding parental tumors. Transcriptomic profiling further revealed gene expression signatures associated with GIST recurrence risk and imatinib resistance. Importantly, the 3DP-GIST models demonstrated the capacity to provide precise, individualized treatment recommendations within 10 days post-surgery, potentially reducing treatment delays and improving patient outcomes. CONCLUSIONS: Overall, the 3DP-GIST model represents a robust and efficient platform for evaluating patient-specific drug sensitivities in vitro, thereby guiding personalized therapeutic strategies for GIST patients.